The role of human capital for AI adoption: evidence from French firms

Fontanelli, Luca, Calvino, Flavio, Criscuolo, Chiara ORCID: 0000-0002-0428-7884, Nesta, Lionel and Verdolini, Elena (2024) The role of human capital for AI adoption: evidence from French firms. CEP Discussion Papers (CEPDP2055). London School of Economics and Political Science. Centre for Economic Performance, London, UK.

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Abstract

We leverage a uniquely comprehensive combination of data sources to explore the enabling role of human capital in fostering the adoption of predictive AI systems in French firms. Using a causal estimation approach, we show that ICT engineers play a key role for AI adoption by firms. Our estimates indicate that raising the current average share of ICT engineers in firms not using AI (1.66%) to the level of AI users (6.7%) would increase their probability to adopt AI by 0.81 percentage points - equivalent to an 8.43 percent growth. However, this would imply substantial investments to fill the existing gap in ICT human capital, amounting to around 450.000 additional ICT engineers. We also explore potential mechanisms, showing that the relevance of ICT engineers for predictive AI is driven by the innovative nature of its use, make-vs-buy choices, large availability of data, ICT and R&D intensity.

Item Type:	Monograph (Discussion Paper)
Official URL:	https://cep.lse.ac.uk/_new/publications/discussion...
Additional Information:	© 2024 The Author(s)
Divisions:	Centre for Economic Performance
Subjects:	H Social Sciences > HC Economic History and Conditions
JEL classification:	J - Labor and Demographic Economics > J2 - Time Allocation, Work Behavior, and Employment Determination and Creation; Human Capital; Retirement > J24 - Human Capital; Skills; Occupational Choice; Labor Productivity O - Economic Development, Technological Change, and Growth > O3 - Technological Change; Research and Development > O33 - Technological Change: Choices and Consequences; Diffusion Processes
Date Deposited:	13 Feb 2025 16:03
Last Modified:	13 Feb 2025 16:03
URI:	http://eprints.lse.ac.uk/id/eprint/126787

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